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This paper aims to propose an extensible, service-oriented framework for context-aware data acquisition, description, interpretation and reasoning, which facilitates the development of mobile applications that provide a context-awareness service.

First, the authors propose the context data reasoning framework (CDRFM) for generating service-oriented contextual information. Then they used this framework to composite mobile sensor data into low-level contextual information. Finally, the authors exploited some high-level contextual information that can be inferred from the formatted low-level contextual information using particular inference rules.

The authors take “user behavior patterns” as an exemplary context information generation schema in their experimental study. The results reveal that the optimization of service can be guided by the implicit, high-level context information inside user behavior logs. They also prove the validity of the authors’ framework.

Further research will add more variety of sensor data. Furthermore, to validate the effectiveness of our framework, more reasoning rules need to be performed. Therefore, the authors may implement more algorithms in the framework to acquire more comprehensive context information.

CDRFM expands the context-awareness framework of previous research and unifies the procedures of acquiring, describing, modeling, reasoning and discovering implicit context information for mobile service providers.

Support the service-oriented context-awareness function in application design and related development in commercial mobile software industry.

Extant researches on context awareness rarely considered the generation contextual information for service providers. The CDRFM can be used to generate valuable contextual information by implementing more reasoning rules.

Universiti Sains Malaysia (USM) uses different detection technologies and integrated library systems (ILS) at its four libraries located at different sites. Hence, ubiquitous data management system is required in the four libraries to enable real-time data sharing and tracking among the libraries. The paper aims to discuss these issues.

Proof of concept is used to verify the performance of integration between different detection technologies including barcode, high frequency (HF) and ultra high frequency (UHF) radio frequency identification (RFID) as well as Integrated Library Management Utility (ILMU) and Koha ILSs. Five pilot tests are performed to investigate the speed of the borrowing and returning transactions, the efficiency of security gate to detect non-borrowed items, and the reliability of the ubiquitous data management system.

The HF RFID technology and the proprietary library system have been used in many libraries. The current study proves that the integration of the UHF RFID technology and the Koha open-source ILS, which is named as Total Open-Source Library Automation Solution, can be a novel solution and can serve as a guide for other libraries.

In the current phase of library data management system, it is common to integrate various technologies in improving the efficiency of the library system. But, the combination of Koha with UHF RFID into a single ILS for intra-library automation system has not been proven. This shows the importance of the proposed proven proof of concept that proves such integration is suitable to be implemented at USM libraries and other libraries.

This paper aims to provide an overview of the electronic product code (EPC) and related RFID standards that are currently being rolled out in the retail industry.

It considers the EPC numbering schemes, air interface protocols, middleware aspects as well as scenarios for practical use.

Identifies possibilities and limitations of EPC standards, the current status of technology adoption and future fields of application.

Of interest to those concerned with RFID technology selection and infrastructure development.

The purpose of the paper is to show that smart item technologies, like RFID and sensor networks, are considered the next big step in business process automation. Through automatic real‐time data acquisition, these technologies can provide benefits to a variety of industries by improving the efficiency of their operations. A service‐oriented infrastructure is proposed that enables the integration of RFID, wireless sensor networks and embedded systems technologies with existing business processes.

This paper discusses the system requirements of a smart items infrastructure in detail. Based on these requirements, the overall infrastructure and the constituting components are introduced. Also, using two real‐world scenarios, it is shown how the proposed infrastructure can be used.

The paper found a set of technical requirements for a smart items infrastructure. The research resulted in the architectural design presented.

To the best of one's knowledge, this paper is the first to identify and explain the technical requirements for a holistic smart items infrastructure. The service‐oriented system architecture provides a new approach to a flexible/adaptable infrastructure for ubiquitous computing. By pointing out requirements and open issues, the paper identifies interesting topics for future research in this area.

To provide a new generic model equipped with a “process visualizing” feature by capturing RFID logistics data to represent different logistics processes' status, and sharing them through web‐based technology to supply chain parties.

In order to provide logistics service companies an effective way to manage their logistics processes and help both the up and down stream supply chain parties maximize their activities linkage within the value chain, the proposed system integrates radio frequency identification (RFID) and IT applications to optimize information flow in a supply chain. In doing so, the objective of visualizing logistics process is achieved.

It is found that the proposed model enhanced the performance of third party logistics providers and their supply chain partners in three main areas. They include a significant reduction in inventory level, a substantial drop in the chance of out‐of‐stock and, a significant improvement in the efficiency of delivery. They are among the most critical problems that often exist in a supply chain.

The proposed model requires supply chain participants to share their process data on the web environment so as to achieve the target of collaboration. This demands the need of tight security control over the public internet.

This paper provides useful information and practical guidance for supply chain participants to formulate a “process visualizing featured” information system.

This paper provides a solution to solve common supply chain management problems and offers practical helps to supply chain participants effectively.

Early enterprise resource planning (ERP) systems or, more simply, enterprise systems (ES), were not primarily focused on the supply chain. Their initial focus was to execute and integrate such internally‐oriented applications that support finance, accounting, manufacturing, order entry, and human resources. Having got their internal operations somewhat integrated, many organizations have moved on to address the supply chain with their ES. The Internet has also brought about a revolution in supply chain thinking. Progress toward complete inter‐enterprise integration is measured in years and even decades. In this article, we discuss both the visions firms have for using enterprise systems for supply chain management, and the actual reality of current implementation. We conclude with projections of how enterprise systems will be used for supply chains in the future.

It is crucial for the Indian micro, small and medium enterprises (MSMEs) to implement a few of the most important Industry 4.0 (I4.0) technologies and reap maximum benefits of sustainability. This paper aims to prioritize I4.0 technologies that can help achieve the sustainable operations and sustainable industrial marketing performance of Indian manufacturing MSMEs.

I4.0-based sustainability model was developed. The model was analyzed using data collected from MSMEs by deploying analytic hierarchy process and utility-function-based goal programming. To have a better understanding, interviews were conducted.

Predictive analytics, machine learning and real-time computing were found to be the most important I4.0 technologies for sustainable performance. Sensitivity analysis further confirmed the robustness of the results. Business-to-business sustainable marketing is prioritized as per the sustainability need of operations of industrial MSME buyers.

This study uniquely integrates literature and practitioners’ insights to explore I4.0’s role in MSMEs sustainability in emerging economies. It fills a research gap by aligning sustainability goals of industrial buyers with suppliers’ marketing strategies. Additionally, it offers practical recommendations for implementing technologies in MSMEs, contributing to both academia and industry practices.